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A novel predictive fuzzy adaptive controller for a two-mass drive system

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Języki publikacji
EN
Abstrakty
EN
In the paper, a novel control structure based on the fuzzy logic and model predictive control methodologies for an elastic two-mass drive system is proposed. In order to reduce the computational requirements of the classical MPC methodology, the multi parametric programming (MPT) approach is used. The robustness of the system is ensured by implementation of three MPT controllers generated for different operation points and a supervisory fuzzy system. The main goal of the fuzzy system is suitable shaping of the control signal. The effectiveness of the proposed approach is checked in simulation and experimental tests. In order to show the properties of the proposed control structure, a critical comparison with an adaptive classical MPC controller is carried out. Both control structures are tested taking into account the performance and possibility of real-time implementation.
Rocznik
Strony
37--47
Opis fizyczny
Bibliogr. 29 poz., wykr.
Twórcy
autor
  • Wroclaw University of Science and Technology, Department of Electrical Machines, Drives and Measurements
Bibliografia
  • [1] T. Pajchrowski and K. Zawirski, “Application of artificial neural network for adaptive speed control of PMSM drive with variable parameters”, COMPEL International Journal for Computation and Mathematics in Electrical and Electronic Engineering 32 (4), 1287‒1299, (2013).
  • [2] Y. Yu, Z. Mi, X. Guo, Y. Xu, and T. Zhao, “Low speed control and implementation of permanent magnet synchronous motor for mechanical elastic energy storage device with simultaneous variations of inertia and torque”, IET Electric Power Applications, 10 (3), 172–180, (2016).
  • [3] S. Brock, D. Luczak, K. Nowopolski, T. Pajchrowski, and K. Zawirski, “Two approaches to speed control for multi-mass system with variable mechanical parameters”, IEEE Transactions on Industrial Electronics, 64 (4), 3338–3347, (2017).
  • [4] A. Stînean, C. Bojan-Dragos, R. Precup, S. Preitl, and E. Petriu, “Takagi-Sugeno PD+I fuzzy control of processes with variable moment of inertia”, 2015 International Symposium on Innovations in Intelligent SysTems and Applications (INISTA), 1 -8, (2015).
  • [5] Y.C. Chang and H.M. Yen, “Design of a robust position feedback tracking controller for flexible-joint robots”, IET Control Theory and Applications, 5 (2), 351–363, (2011).
  • [6] B. Brogliato, R. Ortega, and R. Lozano, “Global tracking controllers for flexible-joints manipulators: a comparative study”, Automatica, 7, 941–956, (1995).
  • [7] A. Michael, S. Manzie, and M.C. Good, “Model predictive control for reference tracking on an industrial machine tool servo drive”, IEEE Transactions on Industrial Informatics, 9 (2) 808–816, (2013).
  • [8] R. Montague, C. Bingham, and K. Atallah, “Servo control of magnetic gear”, IEEE/ASME Tran. on Mechatr, 17 (2), 269‒278 (2012).
  • [9] S. Brock, D. Łuczak, T. Pajchrowski, and K. Zawirski, “Selected methods for a robust control of direct drive with a multi-mass mechanical load”, Advanced Control of Electrical Drives and Power Electronic Converters, 75–98, (2017).
  • [10] K. Szabat and T. Orlowska-Kowalska, “Vibration suppression in a two-mass drive system using PI speed controller and additional feedbacks – comparative study”, IEEE Transactions on Industrial Electronics, 54 (2), 1193–1206 (2007).
  • [11] A. Yabuki, T. Yoshioka, K. Ohishi, T. Miyazaki, and Y. Yokokura, “Design method of stable force control system using new resonance ratio control and instantaneous state observer”, 41st Annual Conference of the IEEE Industrial Electronics Society, (2015).
  • [12] T. Orlowska-Kowalska and M. Dybkowski, “Performance analysis of the sensorless adaptive sliding-mode neuro-fuzzy control of the induction motor drive with MRAS-type speed estimator”, Bull. Pol. Ac.: Tech., 60 (1), 61–70 (2012).
  • [13] K. Dróżdż, “Adaptive control of the drive system with elastic coupling using fuzzy Kalman filter with dynamic adaptation of selected coefficients”, Eksploatacja i Niezawodność–Maintenance and Reliability, 17 (4), 561–568, (2015).
  • [14] M. Cychowski and K. Szabat, “Efficient real-time model predictive control of the drive system with elastic transmission”, IET Control Theory & Applications 4 (1), 37–49 (2010).
  • [15] K. Szabat, P. Serkies, and M. Cychowski, “Application of the MPC to the robust control of the two-mass drive system”, IEEE International Symposium on Industrial Electronics, 1901–1906, (2011).
  • [16] J.M. Maciejewski, Predictive Control With Constraints, Prentice Hall 2002.
  • [17] P. Tatjewski, “Advanced control of industrial processes: structures and algorithms”, Springer Science & Business Media, 2007
  • [18] P. Wiatr, M., and P. Kaźmierkowski, “Model predictive control of multilevel cascaded converter with boosting capability–a simulation study”, Bull. Pol. Ac.: Tech., 64 (3), 581–590 (2016).
  • [19] H.S. Molina, J.D. Rojas, and L.M. Tamayo, “Finite set model predictive control to a shunt multilevel active filter”, COMPEL International Journal for Computation and Mathematics in Electrical and Electronic Engineering 34 (1), 279–300 (2015).
  • [20] K. Belda and D. Vošmik, “Explicit generalized predictive control of speed and position of PMSM drives”, IEEE Transactions on Industrial Electronics, 63 (6), 3889–3896, (2016).
  • [21] P. Serkies and K. Szabat, “Application of the MPC controller to the position control of the two-mass drive system”, IEEE Transactions on Industrial Electronics, 60 (9), 3679–3688 (2013).
  • [22] P. Tøndel, T.A. Johansen, and A. Bemporad, “Evaluation of piecewise affine control via binary search tree”, Automatica, 39 (5), 945–950, (2003).
  • [23] A. Bemporad, M. Morari, V. Dua, and E.N. Pistikopoulos, “The explicit linear quadratic regulator for constrained systems”, Automatica, 38 (1) 3–20, (2002).
  • [24] M. Kvasnica, P. Grieder, M. Baotic, and M. Morari, “Multi-parametric toolbox (MPT), HSCC (hybrid systems: computation and control)”, Lecture Notes in Computer Science, 2993, 448‒465, (2004).
  • [25] P. Tøndel, T.A. Johansen, and A. Bemporad, “An algorithm for multi-parametric quadratic programming and explicit MPC solutions”, Automatica, 39 (3), 489‒497 (2003).
  • [26] K. Szabat and T. Orłowska-Kowalska, “Application of the Kalman filters to the high-performance drive system with elastic coupling”, IEEE Trans. on Industrial Electronics, 59 (11), 4226–4235 (2012).
  • [27] M. Richter, M.E. Magaña, O. Sawodny, and T.K.A. Brekken, “Nonlinear model predictive control of a point absorber wave energy converter”, IEEE Trans. on Sustainable Energy, 4(1), 118‒126 (2013).
  • [28] P. Serkies, K. Szabat, and S. Dodds, “Two-mass drive control based on the FDC method with the limitations of the state variables”, Przegląd Elektrotechniczny 89(12), 60‒63 (2013).
  • [29] C. Wang, M. Yang, W. Zheng, J. Long, and D. Xu, “Vibration suppression with shaft torque limitation using explicit MPC-PI switching control in elastic drive systems”, IEEE Trans. on Industrial Electronics, 62 (11), 6855‒6867 (2015).
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0c7f479f-dfa7-4e3e-8209-14322cead5c8
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